COVID’s Impact on Predictive Analytics and Forecasting

The world is a dramatically different place than it was just eighteen months ago. Pre-COVID behaviors and many of the business rules we once relied on are no longer valid. This proved problematic for nearly every company’s analytics and forecasting approaches which are based on historical data. From customer behavior to supply and demand patterns, historical patterns and the assumption of continuity are what give predictive models their power. COVID’s impact on how we now live and work has challenged those patterns—and the forecasts and predictive models companies use for making business decisions.

At our next event, hear two analytics leaders share their story on how COVID disrupted their predictive analytics and forecasting, how they creatively solved the issue, and how it has changed their analytics approach for the long term.

Event Agenda:
11:30 AM – Event Kick-off and Introductions
11:45 AM – Presenter Case Studies
12:30 PM – Panel Q&A with Both Presenters
1:00 PM – Event Wrap-up

Date & Time

  • March 16, 2016
  • 8:00 AM – 10:30 AM

Featured Speaker:

JuJuan

As restrictions around public gatherings fluctuated throughout 2020, so did demand in the food distribution industry. From a precipitous drop in March, to a slow incremental recovery through the summer months, to a full-on splurge in 2021. Developing a strategy for forecasting expected demand was essential to our mission of providing our customers with the service they expect from US Foods which helps them make it.

Gopal

Vyaire Medical

With COVID-19 came the need for Vyaire to dramatically increase production of ventilators and associated supplies. Insight Analytics Platform enabled Vyaire management to make agile decisions based on up-to-date, trusted data. The work also enabled new capabilities that power Machine Learning and enhanced Vyaire’s production output.